Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis

Author(s):  
Youngjin Yoo ◽  
Lisa W. Tang ◽  
Tom Brosch ◽  
David K. B. Li ◽  
Luanne Metz ◽  
...  
2021 ◽  
Vol 8 (5) ◽  
pp. e1051
Author(s):  
Ting-Yi Lin ◽  
Viktoriya Vitkova ◽  
Susanna Asseyer ◽  
Ivette Martorell Serra ◽  
Seyedamirhosein Motamedi ◽  
...  

ObjectiveTo investigate the association of combined serum neurofilament light chain (sNfL) and retinal optical coherence tomography (OCT) measurements with future disease activity in patients with early multiple sclerosis (MS).MethodsWe analyzed sNfL by single molecule array technology and performed OCT measurements in a prospective cohort of 78 patients with clinically isolated syndrome and early relapsing-remitting MS with a median (interquartile range) follow-up of 23.9 (23.3–24.7) months. Patients were grouped into those with abnormal or normal sNfL levels, defined as sNfL ≥/<80th percentile of age-corrected reference values. Likewise, patients were grouped by a median split into those with thin or thick ganglion cell and inner plexiform layer (GCIP), peripapillary retinal nerve fiber layer, and inner nuclear layer in nonoptic neuritis eyes. Outcome parameters were violation of no evidence of disease activity (NEDA-3) criteria or its components.ResultsPatients with abnormal baseline sNfL had a higher risk of violating NEDA-3 (hazard ratio [HR] 2.28, 95% CI 1.27–4.09, p = 0.006) and developing a new brain lesion (HR 2.47, 95% CI 1.30–4.69, p = 0.006), but not for a new relapse (HR 2.21, 95% CI 0.97–5.03, p = 0.058). Patients with both abnormal sNfL and thin GCIP had an even higher risk for NEDA-3 violation (HR 3.61, 95% CI 1.77–7.36, p = 4.2e−4), new brain lesion (HR 3.19, 95% CI 1.51–6.76, p = 0.002), and new relapse (HR 5.38, 95% CI 1.61–17.98, p = 0.006) than patients with abnormal sNfL alone.ConclusionsIn patients with early MS, the presence of both abnormal sNfL and thin GCIP is a stronger risk factor for future disease activity than the presence of each parameter alone.


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